Sarawan Wongsa

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Metabolic flux analysis using 13C-tracer experiments is an important tool in metabolic engineering since intracellular fluxes are non-measurable quantities in vivo. Current metabolic flux analysis approaches are fully based on stoichiometric constraints and carbon atom balances, where the over-determined system is iteratively solved by a parameter(More)
Metabolic flux analysis is important for metabolic system regulation and intracellular pathway identification. A popular approach for intracellular flux estimation involves using ^{13}{\rm C} tracer experiments to label states that can be measured by nuclear magnetic resonance spectrometry or gas chromatography mass spectrometry. However, the bilinear(More)
Metabolic fluxes have been regarded as an important quantity for metabolic engineering as they reveal cause-effect relationships between genetic modifications and resulting changes in metabolic activity and are used as a prerequisite for the design of optimal whole cell biocatalysts. The intracellular fluxes must be estimated due to the inability to measure(More)
This paper presents a method for identifying the optimum structure of Wiener model with piecewise linearisation. The number of piecewise linear functions for estimating the static nonlinear and the maximum lag of the linear dynamic part of the Wiener model are selected by cross-validation based approach. The maximum lag and the number of partitions are(More)
This paper presents the development of control technique for an internal combustion engine which controls fuel injections for various gasoline/ethanol mixtures. Yamaha motorcycle, Spark 135i, is tested to find the injection timing for E0, E20, E85 and E100, respectivelty. The experiments are conducted with a speed upto 8000 rpm and working load between 0(More)
This paper describes a functional fatigue detection system for nonlinear SMA-based control valve. Any drift from the normal behavior of the valve is revealed using a model-based residual generator by means of a nonlinear auto-regressive with eXogenous input (NARX) model. Based on the optimisation property of cumulative sum (CUSUM), an online system for(More)
The data recorded in industry for rotating machine health monitoring are often a large number and unlabelled. It is impractical to label these data manually. Traditionally unsupervised algorithms have been applied to address this challenge. In the situation where relevant features are included or when the features are not selected properly, it could lead to(More)
In this article, a principal component analysis (PCA) based process monitoring approach is proposed for detecting and isolating damaged splitter nozzles in gas turbine combustion chamber. Damage in splitter nozzles can lead to unstable combustion process and had to start-up and result in unplanned shutdown. The present method detects any abnormal(More)
This paper presents an algorithm for quantifying valve stiction in control loop based on linear decrease inertia weight particle swarm optimisation. The amount of stiction present in the valve is estimated by identifying parameters of Kano model which is a two-parameter data-driven stiction modelling based on the parallelogram of MV-PV phase plot.(More)